Image generation via computed tomography system

ABSTRACT

Among other things, computed tomography (CT) systems and/or techniques for generating projections images of an object(s) under examination via a CT system are provided. The projection images of the object may represent a projection of the entire object or merely a portion of the object, such as a slice of the object. A surface about which the projection image is focused is defined and data yielded from a plurality of views of the object is mapped to the surface. In some embodiments, such a mapping comprises mapping data corresponding to a first view and yielded from a first detector cell to a first point on the surface, mapping data corresponding to the first view and yielded from a second detector cell to a second point on the surface, and/or mapping data corresponding to a second view and yielded from the first detector cell to a third point on the surface.

BACKGROUND

The present application relates to radiation systems. It findsparticular application in the context of security imaging, where it maybe desirable to display high resolution two-dimensional (2D) imagesrepresentative of an object to security personnel while utilizingvolumetric data representative of the object for automated threatdetection. However, it may also find applicability in medical fields,industrial fields, and/or other fields where radiation systems areemployed to examine/image an object.

Today, radiation imaging systems such as computed tomography (CT)systems, single-photon emission computed tomography (SPECT) systems,digital projection systems, and/or line-scan systems, for example, areuseful to provide information, or images, of interior aspects of anobject under examination. The object is exposed to rays of radiationphotons (e.g., x-ray photons, gamma ray photons, etc.) and radiationphotons traversing the object are detected by a detector arraypositioned substantially diametrically opposite a radiation sourcerelative to the object. A degree to which the radiation photons areattenuated by the object (e.g., absorbed, reflected, etc.) is measuredto determine one or more properties of the object, or rather aspects ofthe object. For example, highly dense aspects of an object typicallyattenuate more radiation than less dense aspects, and thus an aspecthaving a higher density, such as a bone or metal, for example, may beapparent when surrounded by less dense aspects, such as muscle orclothing.

Radiation imaging systems are utilized in a variety of fields toimage/examine aspects of an object not readily visible to the naked eye.For example, radiation imaging systems are used in security applicationsto identify potential threat items, including weapons and/or explosives,concealed within a suitcase or other object, for example.

Two of the more common types of radiation imaging systems used insecurity applications are CT systems and line-scan systems. Line-scansystems are configured to view the object from a limited number ofview-angles (e.g., typically 1 view-angle) and generate projectionimages (e.g., 2D images) respectively representing a collapsed orflattened, 2D view of the object (e.g., where the densities of aspectsof an object through a line in which radiation travels are integratedand represented as a single point on the 2D image). Such systems areparticularly valuable for generating high resolution 2D images fordisplay to security personnel responsible for identifying potentialthreat objects.

CT systems are configured to view an object from a greater number ofview-angles than line-scan systems and to generate volumetric datarepresentative of the object. In this way, a three-dimensional (3D)image of the object can be created and properties of respective aspectswithin the object, such as density information, z-effective information,shape characteristics, etc. can be determined. Using one or more ofthese properties, automated threat analysis can be performed todetermine if the object is a potential threat item. Moreover, 2Dprojection images or 3D volumetric images can be obtained from CTsystems that are representative of the object (e.g., although typicallysuch images are of a lower resolution than the projection imagesgenerated by line-scan systems due to, among other things, differencesin the resolution of CT detector arrays relative to detector arraysutilized in line-scan systems).

While automatic threat analysis algorithms have proven useful toidentify potential threat items, it is sometimes desirable for asecurity screener to view images of the objects or aspects concealedtherein. Accordingly, the resolution of images produced by a radiationimaging system is sometimes an important consideration when selectingwhether to implement a line-scan system or a CT system in anenvironment.

SUMMARY

Aspects of the present application address the above matters, andothers. According to one aspect, a method for generating a projectionimage from volumetric data is provided. The method comprises acquiringvolumetric data yielded from an examination of an object via radiationand defining a surface about which a projection image of the object isfocused. The method also comprises mapping a first portion of thevolumetric data, corresponding to a first view, to the surface andmapping a second portion of the volumetric data, corresponding to asecond view, to the surface. The method further comprises generating aprojection image based upon the mapping a first portion and the mappinga second portion.

According to another aspect, a method for generating a projection imagefrom volumetric data is provided. The method comprises acquiringvolumetric data yielded from an examination of an object via radiationand defining a surface about which a projection image of the object isfocused. The method also comprises, for a first view, determining afirst trajectory between a radiation source emitting the radiationduring the first view and a predefined location on a first detectorcell, identifying a first intersection between the first trajectory andthe surface, and mapping a first portion of the volumetric data, yieldedfrom the first detector cell and corresponding to the first view, to thefirst intersection. The method also comprises, for a second view,determining a second trajectory between the radiation source during thesecond view and the predefined location on the first detector cell,identifying a second intersection between the second trajectory and thesurface, and mapping a second portion of the volumetric data, yieldedfrom the first detector cell and corresponding to the second view, tothe second intersection. The method further comprises generating aprojection image based upon the mapping a first portion and the mappinga second portion.

According to another aspect, a method is provided. The method comprisesextracting, from volumetric data yielded from an examination of anobject via radiation, a portion of the volumetric data indicative of aslice of the object that is of interest. The method also comprisedefining a surface about which a sliced projection image of the slice isfocused and mapping a first portion of the portion of the volumetricdata, corresponding to a first view, to the surface. The method furthercomprises mapping a second portion of the portion of the volumetricdata, corresponding to a second view, to the surface and generating thesliced projection image based upon the mapping a first portion and themapping a second portion.

Those of ordinary skill in the art may appreciate still other aspects ofthe present application upon reading and understanding the appendeddescription.

FIGURES

The application is illustrated by way of example and not limitation inthe figures of the accompanying drawings, in which like referencesgenerally indicate like elements and in which:

FIG. 1 is a schematic block diagram illustrating an example environmentwhere a CT system such as described herein may be implemented.

FIG. 2 is a functional diagram illustrating a helical examinationperformed via a CT system.

FIG. 3 is a functional diagram illustrating a helical examinationperformed via a CT system.

FIG. 4 is a functional diagram illustrating an example mapping for afirst view.

FIG. 5 is a functional diagram illustrating an example mapping for afirst view.

FIG. 6 is a functional diagram illustrating an example mapping for afirst view.

FIG. 7 is an example projection image having data from a plurality ofviews mapped thereto.

FIG. 8 is a flow diagram illustrating an example method for generating aprojection image from volumetric data.

FIG. 9 is a flow diagram illustrating an example method for generating aprojection image from volumetric data.

FIG. 10 is a flow diagram illustrating an example method for generatinga sliced projection image from volumetric data.

FIG. 11 is an illustration of an example computer-readable mediumcomprising processor-executable instructions configured to embody one ormore of the provisions set forth herein.

DESCRIPTION

The claimed subject matter is now described with reference to thedrawings, wherein like reference numerals are generally used to refer tolike elements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providean understanding of the claimed subject matter. It may be evident,however, that the claimed subject matter may be practiced without thesespecific details. In other instances, structures and devices areillustrated in block diagram form in order to facilitate describing theclaimed subject matter.

The present disclosure relates to a computed tomography (CT) system,such as may be employed in security applications for threat-detection.The CT system is configured to generate volumetric data, indicative ofan object under examination, from which 2D projection images and/or 3Dvolumetric images of the object can be generated. The projection imagesmay represent an entire object or merely a slice of the object. Aprojection image representative of merely a slice of the object may bereferred to, at times, as a sliced projection image. In someembodiments, projection images resulting from the examination of anobject are of a higher resolution than conventionally attainable via CTsystems. For example, the CT system may be configured to generateprojection images having a spatial frequency of at least 2.5 line pairsper centimeter (2.5 LP/cm).

As provided for herein, an object to be examined by the CT system isinserted into the CT system and is helically examined (e.g., by rotatinga radiation source and detector array in an x,y plane about an axis ofrotation extending in a z-direction while translating the object in thez-direction) and/or examined in a step-and-shoot manner (e.g., where theobject is translated in the z-direction between examinations by theradiation source and detector array). In this way, the object is viewedfrom a plurality of view-angles to generate volumetric data indicativeof the object.

To generate the projection image from the volumetric data, a surface isdefined. The surface describes a topological manifold about which theprojection image is focused. Thus, aspects of the object contacting thesurface may be in-focus in the projection image while aspects of theobject more distant from the surface may appear out of focus (e.g., mayappear more blurry and/or jagged). In some embodiments, the surfaceextends (e.g., to some degree) in a direction parallel to the axis ofrotation (e.g., extending in the z-direction).

The surface may be arbitrarily defined or may be defined based uponinformation known about the object. By way of example, using anautomated threat detection system, a region of interest (e.g., gun,sheet explosive, etc.) within the object may be identified, and asurface may be defined based upon the region of interest (e.g., to atleast partially include the region of interest). The surface may bestatically defined for respective objects undergoing examination or maybe dynamically defined on an object-by-object or aspect-by-aspect basis,for example. Moreover, in some embodiments, multiple projection imagesrepresenting a same object may be generated by defining multiplesurfaces. In some embodiments, respective projection images mayrepresent a slice of the object (e.g., where a first projection imagerepresents a first slice and a second projection image represents asecond slice different than the first slice).

Data corresponding to rays emitted over a defined set of view-angles maybe mapped to the surface to generate a projection image focused on thesurface. To perform the mapping, the trajectory of rays emitted over adefined set of view-angles and intersecting the detector array atpredefined locations is determined. By way of example, in someembodiments, the detector array is comprised of a plurality of detectorcells (e.g., typically arranged in rows and columns). For a firstview-angle of the defined set of view-angles, a first trajectory fromthe radiation source to a center of a first detector cell is determinedto identify a first ray (e.g., following the first trajectory) and asecond trajectory from the radiation source to a center of a seconddetector cell is determined to identify a second ray (e.g., followingthe second trajectory). Such a process may be repeated for respectivedetector cells (e.g., such that there is a one-to-one ratio betweendetector cells and trajectories for the first view-angle).

Next, the intersection of the surface and respective rays identifiedfrom the first view-angle are determined to map data associated with thefirst view-angle to the surface. By way of example, first datacorresponding to the first view and yielded from the first detector cellis mapped to a first point where the first ray intersects the surfaceand second data corresponding to the first view and yielded from thesecond detector cell is mapped to a second point where the second rayintersects the surface.

A similar process of mapping the data to the surface may be performedfor a defined number of view-angles. For example, for a secondview-angle of the defined set of view-angles, a third trajectory fromthe radiation source to the center of the first detector cell isdetermined to identify a third ray (e.g., following the thirdtrajectory) and a fourth trajectory from the radiation source to thecenter of the second detector cell is determined to identify a fourthray (e.g., following the fourth trajectory). Third data corresponding tothe second view and yielded from the first detector cell is mapped to athird point where the third ray intersects the surface and fourth datacorresponding to the second view and yielded from the second detectorcell is mapped to a fourth point where the fourth ray intersects thesurface.

Such mapping facilitates the generation of the projection image. By wayof example, an intensity of a first pixel of the projection imagerepresenting the first point may be based upon the first data and anintensity of a second pixel of the projection image representing thesecond point may be based upon the second data. Data for regions of thesurface not intersecting a ray may be estimated using one or moreinterpolation techniques.

Referring to FIG. 1, an example environment 100 of a CT system asprovided for herein is illustrated. It may be appreciated that theenvironment 100 merely provides an example arrangement and is notintended to be interpreted in a limiting manner, such as necessarilyspecifying the location, inclusion, and/or relative position of thecomponents depicted therein. By way of example, in some embodiments, adata acquisition component 120 is part of a detector array 118 and/or islocated on a rotating gantry 106 of the CT system.

In the example environment 100, an examination unit 102 of the radiationsystem is configured to examine objects 104. The examination unit 102comprises a rotating gantry 106 and a (stationary) support structure 108(e.g., which may encase and/or surround at least a portion of therotating gantry 106 (e.g., as illustrated with an outer, stationaryring, surrounding an outside edge of an inner, rotating ring)). Duringan examination of an object 104, the object 104 is placed on a supportarticle 110, such as a bed or conveyor belt, for example, that istranslated through an examination region 112 (e.g., a hollow bore in therotating gantry 106), where the object 104 is exposed to radiation 120.

The rotating gantry 106 may surround a portion of the examination region112 and may comprise a radiation source 116 (e.g., an ionizing radiationsource such as an x-ray source and/or gamma-ray source) and the detectorarray 118. The detector array 118 is typically mounted on asubstantially diametrically opposite side of the rotating gantry 106relative to the radiation source 116, and during an examination of theobject 104, the rotating gantry 106 (e.g., including the radiationsource 116 and detector array 118) is rotated about the object 104. Aswill be further described with respect to FIG. 2, such rotation of therotating gantry 106 in combination with the translation of the object104 through the examination region 112 causes the object to be helicallyexamined (e.g., in a continuous or step-and-shoot fashion). Because theradiation source 116 and the detector array 118 are mounted to a samerotating gantry 106, a relative position between the detector array 118and the radiation source 116 is substantially maintained during therotation of the rotating gantry 106.

During the examination of the object 104, the radiation source 116 emitscone-beam and/or fan-beam radiation configurations from a focal spot ofthe radiation source 116 (e.g., a region within the radiation source 116from which radiation 120 emanates) into the examination region 112. Suchradiation 120 may be emitted substantially continuously and/or may beemitted intermittently (e.g., a brief pulse of radiation 120 is emittedfollowed by a resting period during which the radiation source 116 isnot activated). Further, the radiation 120 may be emitted at a singleenergy spectrum or multiple energy spectrums depending upon, among otherthings, whether the CT system is configured as a single-energy CT systemor a multi-energy (e.g., dual-energy) CT system.

As the emitted radiation 120 traverses the object 104, the radiation 120may be attenuated differently by different aspects of the object 104.Because different aspects attenuate different percentages of theradiation 120, the number of photons detected by the respective detectorcells of the detector array 118 may vary. For example, more denseaspects of the object(s) 104, such as a bone or metal plate, mayattenuate more of the radiation 120 (e.g., causing fewer photons toimpinge upon a region of the detector array 118 shadowed by the moredense aspects) than less dense aspects, such as skin or clothing.

Radiation detected by the detector array 118 may be directly convertedand/or indirectly converted into analog signals that can be transmittedfrom the detector array 118 to the data acquisition component 120operably coupled to the detector array 118. The analog signal(s) maycarry information indicative of the radiation detected by the detectorarray 118 (e.g., such as an amount of charge measured over a samplingperiod and/or an energy level of detected radiation). The dataacquisition component 120 is configured to convert the analog signalsoutput by the detector array 118 into digital signals and/or to compilesignals that were transmitted within a predetermined time interval, ormeasurement interval, using various techniques (e.g., integration,photon counting, etc.). The compiled signals are typically in projectionspace and are, at times, referred to as projections. A projection may berepresentative of the information collected or measurements acquired byrespective detector cells of the detector array 118 during a onetime-interval or view, where a view corresponds to data collected whilethe radiation source 160 was at a particular view-angle relative to theobject 104.

The projections generated by the data acquisition component 120 may betransmitted to an object analysis component 122 configured to assembletwo or more projections to generate a volumetric representation of theobject 104 in projection space and/or in image space (e.g., where theprojections are converted to image space by reconstructing theprojections via analytic, iterative, or other reconstruction techniques(e.g., tomosynthesis reconstruction, backprojection, etc.)). In thisway, volumetric data indicative of the object 104 is yielded from theexamination.

In some embodiments, the object analysis component 122 is furtherconfigured to utilize the volumetric data (e.g., in projection spaceand/or image space) to determine or estimate one or more properties ofitems within the object 104. By way of example, in a securityenvironment, the object analysis component 122 (e.g., at times referredto as an automated threat detection system) may be configured toapproximate, among other things, density information, z-effectiveinformation, and/or shape characteristics of various items within theobject (e.g., a suitcase, bag, etc.). Using such information and/orcharacteristics, the object analysis component 122 may determine if theobject 104 comprises a potential threat item (e.g., such as a weaponand/or explosive), which may be flagged for further inspection. Forexample, the object analysis component 122 may compare the approximateddensities or other properties of respective items to a list of knownproperties for threat items. If one or more of the approximateddensities corresponds to (e.g., matches within a specified deviation) adensity on the list, the object analysis component 122 may alertsecurity personnel of the correspondence and/or alert an image generatorof the potential identification, for example.

The example CT system further comprises an image generator 124configured to generate one or more projection images of the object 104using the projections yielded from the data acquisition component 120and/or information provided by the object analysis component 122.

As will be described in more detail below, to generate a projectionimage, a surface is defined about which the projection image is to befocused. The surface may be planar or non-planar and, in someembodiments, extends (e.g., to some degree) in a direction parallel tothe axis of rotation. Moreover, the surface may be user-defined or maybe defined as a function of information provided by the object analysiscomponent 122. By way of example, in some embodiments, the imagegenerator 124 may define a surface to include a portion of the object104 identified as a potential threat item by the object analysiscomponent 122.

In some embodiments, as further described by FIGS. 4-6, data yieldedfrom a plurality of views (e.g., corresponding to the radiation sourceat a plurality of view-angles) is mapped to the surface and theprojection image is generated based upon the mapping. By way of example,first data yielded from a first detector cell during a first view may bemapped to a first point on the surface (e.g., based upon a trajectory ofa first ray intersecting a center of the first detector cell during thefirst view) and a characteristic of a first pixel representing the firstpoint may be determined based upon the first data. As another example,second data yielded from the first detector cell during a second viewmay be mapped to a second point on the surface (e.g., based upon atrajectory of a second ray intersecting the center of the first detectorcell during the second view) and a characteristic of a second pixelrepresenting the second point may be determined based upon the seconddata. In this way, the image generator 124 uses data acquired during aplurality of views to generate the projection image, for example.

The example environment 100 further comprises a terminal 126, orworkstation (e.g., a computer), that may be configured to receive aprojection image(s) indicative of the object 104 (e.g., output by theimage generator 124) and/or to receive information related to whetherthe object 104 comprises an item of potential interest, for example(e.g., output from the object analysis component 122). At least some ofthe received information/images may be provided by the terminal 126 fordisplay on a monitor 128 to a user 130 (e.g., security personnel,medical personnel, etc.). In this way, the user 130 can inspect theimage(s) to identify areas of interest within the object 104 while alsobeing provided information regarding potential items of interest thathave been identified via an automated process, for example. The terminal126 can also be configured to receive user input which can directoperations of the examination unit 102 (e.g., a speed to rotate, a speedand direction of a support article 110, etc.), for example.

In the example environment 100, a controller 132 is operably coupled tothe terminal 126. The controller 132 may be configured to controloperations of the examination unit 102, for example. By way of example,in one embodiment, the controller 132 may be configured to receiveinformation from the terminal 126 and to issue instructions to theexamination unit 102 indicative of the received information (e.g.,adjust a speed of a conveyor belt).

FIG. 2 is a functional diagram 200 of a helical examination performedvia a CT system, such as in security applications and/or medicalapplications, for example. In such a system, an object 202 (e.g., 104 inFIG. 1) under examination is translated 204 in a direction substantiallyparallel to an axis of rotation (e.g., along a z-axis), via a supportarticle 206 (e.g., 110 in FIG. 1). The object 202 is exposed toradiation 214 (e.g., 120 in FIG. 1) while the object 202 is beingtranslated. That is, one or more radiation sources 208 (e.g., 116 inFIG. 1) are configured to emit radiation 214, causing the object 202 tobe exposed to radiation 214. A detector array 210 (e.g., 118 in FIG. 1),mounted on a substantially diametrically opposite side of the object 202relative to the radiation source(s) 208, is configured to detectradiation 214 that has traversed the object 202. In this way, byemitting and detecting radiation 214, the object 202 is examined.

In a CT system, the radiation source(s) 208 and the detector array 210are typically rotated about the object 202 in a plane (e.g., typicallydefined as an x-y plane) via a rotating gantry (e.g., 106 in FIG. 1)during the examination. In this way, the radiation source 208 views theobject 202 from a plurality of view-angles to develop volumetric dataregarding the object 202. Further, in an environment where the object202 is translated in the z-direction (e.g., continuously or in astep-and-shoot manner), such a rotation may cause the radiationsource(s) 208 and/or the detector array 210 to follow a spiral orhelical-like trajectory 212 relative to the object (e.g., where theradiation source(s) 208 and detector array 210 do not move in thez-direction, and thus the helical trajectory is established by thecombination of the x,y rotation of the radiation source(s) 208 anddetector array 210 and the z-direction translation 204 of the object202).

FIG. 3 illustrates another functional diagram 300 further describing thetrajectory of a radiation source (e.g., 208 in FIG. 2) and a detectorarray 302 (e.g., 210 in FIG. 2). The detector array 302 and radiationsource rotate in an x,y plane about an object under examination while anobject (e.g., 104 in FIG. 1) is translated in a z-direction (e.g.,perpendicular to the x,y plane), causing the radiation source and thedetector array 302 to follow a helical-like trajectory 306 relative tothe object. For purposes of illustration, merely a surface 304 ofinterest within the object is illustrated. It may be appreciated thatwhile FIG. 3 describes a surface 304 within the object, in someembodiments, the surface about which the projection image is focused maynot be located within an object. For example, the surface 304 may belocated in a region typically occupied by the support article (e.g., 110in FIG. 1).

The black dots along the helical-like trajectory 306 represent theradiation source at various times during the examination and correspondto different view-angles. For example, V− may represent the radiationsource at a first view-angle, V may represent the radiation source at asecond view-angle, and V+ may represent the radiation source at a thirdview-angle. Data generated while the radiation source is at the firstview-angle may be compiled into a first view, data generated while theradiation source is at the second view-angle may be compiled into asecond view, etc. The number of views (e.g., and thus the number ofview-angles) may be based upon the sampling frequency of the detectorcells and/or a desired signal-to-noise ratio of the CT system, forexample.

In this diagram 300, the detector array 302 (e.g., 210 in FIG. 2) isillustrated as being planar. However, it may be appreciated that in someembodiments, a detector array of a CT system is substantially arcuate inshape as illustrated in FIGS. 1 and 2.

A detection surface of the detector array 302 generally extends in thex-direction and the z-direction, where the z-direction is typically adirection in which the object is translated. The detector array 302generally comprises detector cells 308 arranged in columns and rows. Arow of detectors cells 308 generally extends in the x-direction and acolumn of detector cells 308 generally extends in the z-direction.Typically, a distance that the object is translated between two adjacentviews is less than the row pitch (e.g., where row pitch is defined asthe distance from a center of a first row to a center of an adjacentrow). By way of example, in some embodiments, the distance that theobject is translated between two adjacent views is approximately 5% ofthe row pitch. Accordingly, a point in the object shadows a same row ofdetector cells for approximately 20 views. It is to be appreciated,however, that this is merely a non-limiting example.

During respective views, all or substantially all of the detector array302 is illuminated by the radiation. For example, the radiation sourcemay continually or intermittently emit cone-beam radiation that exposesnearly all of the detector array 302 to radiation.

Turning to FIGS. 4-6, functional diagrams 400, 500, and 600 illustratehow data yielded from the detector array 302 is mapped to the surface304 (e.g., by the image generator 124 in FIG. 1) to facilitate thegeneration of a projection image focused on the surface 304. In someembodiments, the surface 304 extends in a direction parallel to the axisof rotation (e.g., parallel to a z-axis) and lies within an x,z plane.In other embodiments, the surface 304 may be non-planar and/or may liewithin a different plane (e.g., such as a y,z plane). In someembodiments, the surface 304 lies within an object under examination. Inother embodiments, the surface 304 may not lie within the object. Forexample, the surface 304 may be spatially coincident with a supportarticle (e.g., 110 in FIG. 1) translating the object.

In some embodiments, a set of views of interest (e.g., and thus thecorresponding view-angles of interests) are defined based upon theorientation of the surface 304. By way of example, a first set of viewsmay be of interest when the surface lies within an x,z plane and asecond set of views (e.g., different than the first set of views) may beof interest when the surface lies within an y,z plane. Moreover, anumber of views of interest may be predefined (e.g., at time ofmanufacturing), may be selected at random, and/or may be selected basedupon some predetermined criteria (e.g., voltage applied to the radiationsource, orientation of the surface, speed of rotation, speed oftranslation, desired resolution, etc.).

For respective views of the set of views, data associated with the viewis mapped to the surface 304. By way of example, referring to FIG. 4, afunctional diagram 400 describing an example mapping for a first view isillustrated. During the first view, the radiation source is assumed tobe positioned at a first view-angle V−. It may be appreciated that inpractice, due to the continuous rotation of the radiation source, thefirst view may correspond to a first range of view-angles. However, forpurposes of the calculation, the radiation source is assumed to bepositioned at the first view-angle during the first view (e.g., whichmay be a center of the range).

To map the data associated with the first view to the surface 304, thetrajectories of one or more rays impinging predefined locations ondetector array 302 are determined. By way of example, the trajectory ofa first ray 310 a, emitted from the radiation source while at the firstview-angle V−, to a center of a first detector cell is determined toidentify a first location 312 a where the first ray 310 a intersectedthe surface 304. As another example, the trajectory of a second ray 310b, emitted from the radiation source while at the first view-angle V−,to a center of a second detector cell is determined to identify a secondlocation 312 b where the second ray 310 b intersected the surface 304.As yet another example, the trajectory of a third ray 310 c, emittedfrom the radiation source while at the first view-angle V−, to a centerof a third detector cell is determined to identify a third location 312c where the third ray 310 c intersected the surface 304. Determiningsuch trajectories may be repeated for a plurality of detector cells,such as respective detector cells 308 of the detector array 302.

Data yielded from respective detector cells 308 during the first view ismapped to the identified locations where the rays 310 intersected thesurface 304. By way of example, data yielded from the first detectorcell during the first view is mapped to the first location 312 a, anddata yielded from the second detector cell during the first view ismapped to the second location 312 b. Data yielded from the thirddetector cell during the first view is mapped to the third location 312c. Such mapping may be repeated for the plurality of detector cells, forexample.

A similar process may be performed for a second view and a third view.By way of example, referring to FIG. 5, a functional diagram 500describing an example mapping for a second view is illustrated. Duringthe second view, the radiation source is assumed to be positioned at asecond view-angle V.

To map the data associated with the second view to the surface 304, thetrajectory of one or more rays impinging the predefined locations ondetector array 302 are determined. By way of example, the trajectory ofa fourth ray 314 a, emitted from the radiation source while at thesecond view-angle V, to a center of the first detector cell isdetermined to identify a fourth location 316 a where the fourth ray 314a intersected the surface 304. As another example, the trajectory of afifth ray 314 b, emitted from the radiation source while at the secondview-angle V, to a center of the second detector cell is determined toidentify a fifth location 316 b where the fifth ray 314 b intersectedthe surface 304. As yet another example, the trajectory of a sixth ray314 c, emitted from the radiation source while at the second view-angleV, to a center of the third detector cell is determined to identify asixth location 316 c where the sixth ray 314 c intersected the surface304. Determining such trajectories may be repeated for the plurality ofdetector cells.

It may be appreciated that for ease of understanding, solid dotsrepresenting the locations 312 a-c where the first, second and thirdrays 310 a-c intersected the surface 304 have been imposed on thesurface 304 in FIG. 5 to illustrate a change in locations between thefirst and second views.

Data yielded from respective detector cells 308 during the second viewis mapped to the identified locations where the rays 314 intersected thesurface 304. By way of example, data yielded from the first detectorcell during the second view is mapped to the fourth location 316 a, anddata yielded from the second detector cell during the second view ismapped to the fifth location 316 b. Data yielded from the third detectorcell during the second view is mapped to the sixth location 316 c. Suchmapping may be repeated for the plurality of detector cells, forexample.

Referring to FIG. 6, a functional diagram 600 describing an examplemapping for a third view is illustrated. During the third view, theradiation source is assumed to be positioned at a third view-angle V+.

To map the data associated with the third view to the surface 304, thetrajectory of one or more rays impinging the predefined locations ondetector array 302 are determined. By way of example, the trajectory ofa seventh ray 318 a, emitted from the radiation source while at thethird view-angle V+, to a center of the first detector cell isdetermined to identify a seventh location 320 a where the seventh ray318 a intersected the surface 304. As another example, the trajectory ofan eighth ray 318 b, emitted from the radiation source while at thethird view-angle V+, to a center of the second detector cell isdetermined to identify a eighth location 320 b where the eighth ray 318b intersected the surface 304. As yet another example, the trajectory ofa ninth ray 318 c, emitted from the radiation source while at the thirdview-angle V+, to a center of the third detector cell is determined toidentify a ninth location 320 c where the ninth ray 318 c intersectedthe surface 304. Determining such trajectories may be repeated for theplurality of detector cells.

It may be appreciated that for ease of understanding, solid dotsrepresenting the locations 312 a-c where the first, second, and thirdrays 310 a-c intersected the surface 304 and hollow dots representingthe locations 316 a-c where the fourth, fifth, and sixth rays 314 a-cintersected the surface 304 have been imposed on the surface 304 in FIG.6 to illustrate changes in locations between the first, second, andthird views.

Data yielded from respective detector cells 308 during the third view ismapped to the identified locations where the rays 318 intersected thesurface 304. By way of example, data yielded from the first detectorcell during the third view is mapped to the seventh location 320 a, anddata yielded from the second detector cell during the third view ismapped to the eighth location 320 b. Data yielded from the thirddetector cell during the third view is mapped to the ninth location 320c. Such mapping may be repeated for the plurality of detector cells, forexample.

It may be appreciated that while the example functional diagrams 400,500, and 600 illustrate the mappings of merely three detector cells overthree views (e.g., to derive data for nine locations on the surface),the number of detectors cells that are mapped to the surface and/or thenumber of views being mapped may be substantially greater, such thatdata is available for a majority of the surface (e.g., dots cover asubstantial majority of the surface)

It may be appreciated that when developing the projection image from thedata based upon the mappings described above, a characteristic(s) of apixel of the projection image may be based upon the data mapped to aregion of the surface represented by the pixel. For example, referringto FIG. 7, an example projection image 700 depicting the surface 304 isillustrated. The projection image 700 comprises a grid of pixels 702,wherein respective pixels 702 represent a region of the surface 304.

Based upon, among other things, the size of the object, a width of thedetector array relative to a width of the object, a desired resolution,a rotational speed of the rotating gantry, a translational speed of theobject, a number of views that are mapped to the surface, etc., pixels702 of the projection image 700 may correspond to a region of thesurface to which no data has been mapped, may correspond to a region ofthe surface to which little data has been mapped (e.g., merely one ofthe identified rays intersect the surface within the region representedby the pixel), or may respond to a region of the surface to which aplurality of data has been mapped (e.g., two or more identified raysintersect the surface within the region represented by the pixel).

As an example, a first pixel 702 a may represent a region of the surfaceto which merely a limited amount of data has been mapped. That is, thefirst pixel 702 a may represent a region of the surface intersected bymerely one of the identified ray (e.g., at the first intersection 312a). Accordingly, one or more characteristics of the first pixel 702 a,such as hue, saturation, intensity, etc., may be determined based uponthe limited amount of data (e.g., the data generated by a first detectorcell during a first view).

Other pixels may represent a region of the surface to which a greateramount of data has been mapped. By way of example, a second pixel 702 bmay represent a region of the surface intersected by a first set ofidentified rays (e.g., at the sixth intersection 316 c and the seventhintersection 320 a). Accordingly, one or more characteristics of thesecond pixel 702 b may be determined based upon the data correspondingto one or more of the first set of identified rays. By way of example,data generated by the third detector cell during the second view anddata generated by the first detector cell during the third view may besummed, averaged, or otherwise compiled to determine one or morecharacteristics of the second pixel 702 b. As another example, merelythe data generated by the third detector cell during the second view orthe data generated by the first detector cell during the third view maybe used to determine one or more characteristics of the second pixel 702b. In still other embodiments, kernel based interpolation techniquesand/or other interpolation techniques can be used to interpolate theavailable data (e.g., corresponding to a region of the surfacerepresented by the pixel) and/or to determine one or morecharacteristics of the first pixel 702 a, the second pixel 702 b, thethird pixel 702 c.

Still other pixels may represent a region of the surface to which nodata has been mapped (e.g., none of the identified rays intersect aregion of the surface represented by a third pixel). In situations wherelittle to no data is available for a region of the surface, for example,one or more interpolation techniques may be performed on the data mappedto the surface to estimate data for a region to which little to no datahas been mapped. By way of example, a kernel based interpolation can beperformed where data corresponding to locations in a neighborhood of theempty region is weighted based upon the proximity of the location to theempty region and a weighted average is computed using the weighted data.As another example, data corresponding to locations in a neighborhood ofthe empty region is averaged (e.g., without weights) to estimate datafor the region to which little to no data has been mapped. As stillanother example, a nearest neighbor approach may be taken, where datafor a region to which little to no data has been mapped is estimatedbased upon a nearest location to which data has been mapped. In thisway, one or more characteristics for a pixel representing a region forwhich little to no data is available is determined based upon datacorresponding to a different region of the surface represented by one ormore pixels adjacent the pixel.

Referring to FIG. 8, an example method 800 for generating a projectionimage from volumetric data is illustrated. The example method 800 beginsat 802, and volumetric data of an object is acquired at 804. Thevolumetric data (e.g., in projection space) is yielded fromvolumetrically examining an object via radiation. Such an examinationmay comprise emitting fan-beam or cone-beam radiation from a radiationsource whose position is varied relative to the object to cause theobject to be examined from a plurality of view-angles. In someembodiments, the object may be substantially stationary during theexamination. In other embodiments, the object may be substantiallycontinuously translated (e.g., in a z-direction) during an examinationwhile the radiation source is rotated in a plane (e.g., extending in thex and y directions). In still other embodiments, the object may beperiodically and/or intermittently translated during the examination,such as according to a step-and-shoot-approach. In this way, byvolumetrically examining the object via radiation, volumetric data isgenerated regarding the object.

At 806 a surface about which the projection image is to be focused isdefined. The surface describes a topological manifold, which may beplanar or non-planar. The surface may be defined by a user (e.g., basedupon visualizing the volumetric data), may be defined based uponidentified contents of the object (e.g., such as identified by using anobject analysis component that analyzes the volumetric data and/orimages resulting therefrom to identity potential items of interest), maybe defined at random, and/or may be pre-defined (e.g., such as at thetime of manufacturing and/or prior to an examination of the object).

At 808, a first portion of the volumetric data, corresponding to a firstview, is mapped to the surface. By way of example, as described withrespect to FIG. 4, data yielded from respective detector cells andcorresponding to a first view of the object (e.g., when the radiationsource was at a first view-angle relative to the object) may be mappedto the surface by computing the intersection of predefined rays with thesurface. By way of example, the trajectory of rays impinging a center ofrespective detector cells may be determined and data yielded fromrespective detector cells during the first view may be mapped to alocation on the surface where the corresponding ray intersected thesurface. For example, the trajectory of a first ray impinging a centerof a first detector cell may be determined, and data yielded from thefirst detector cell during the first view may be mapped to a locationwhere the first ray intersected the surface. As another example, thetrajectory of a second ray impinging a center of a second detector cellmay be determined, and data yielded from the second detector cell duringthe first view may be mapped to a location where the second rayintersected the surface. It may be appreciated that while reference ismade herein to determining the trajectory of rays impinging a center ofrespective detector cells, other predefined locations on the detectorarray (e.g., or on respective detector cells) may instead be used. Forexample, the trajectory of rays impinging a corner of respectivedetector cells may be computed instead of computing the trajectory ofrays impinging a center of respective detector cells.

At 810 in the example method 800, a second portion of the volumetricdata, corresponding to a second view, is mapped to the surface. By wayof example, as described with respect to FIG. 5, data yielded fromrespective detector cells and corresponding to a second view of theobject (e.g., when the radiation source was at a second view-anglerelative to the object) may be mapped to the surface by computing theintersection of predefined rays with the surface. By way of example, thetrajectory of rays impinging a center of respective detector cells maybe determined and data yielded from respective detector cells during thesecond view may be mapped to a location on the surface where thecorresponding ray intersected the surface. For example, the trajectoryof a third ray impinging the center of the first detector cell may bedetermined, and data yielded from the first detector cell during thesecond view may be mapped to a location where the third ray intersectedthe surface. As another example, the trajectory of a fourth rayimpinging the center of the second detector cell may be determined, anddata yielded from the second detector cell during the second view may bemapped to a location where the second ray intersected the surface.

At 812 in the example method 800, a projection image is generated basedupon mapping the first portion of the volumetric data and the secondportion of the volumetric data to the surface. For example, one or morecharacteristics of the respective pixels of the projection image may bedetermined based upon the mapping as described with respect to FIG. 7.

The example method ends at 814.

Referring to FIG. 9, another example method 900 for generating aprojection image from volumetric data is illustrated. The example method900 begins at 902, and volumetric data of an object is acquired at 904.In some embodiments, the volumetric data is acquired from a detectorarray comprising a plurality of detector cells respectively configuredto generate information regarding radiation impinging thereon. Thus, afirst detector cell generates information regarding radiation thatimpinges the first detector cell and a second detector cell generatesinformation regarding radiation that impinges the second detector cell.

At 906 a surface about which the projection image is to be focused isdefined. The surface describes a topological manifold, which may beplanar or non-planar. The surface may be defined by a user (e.g., basedupon visualizing the volumetric data), may be defined based uponidentified contents of the object (e.g., such as identified by using anobject analysis component that analyzes the volumetric data and/orimages resulting therefrom to identity potential items of interest), maybe defined at random, and/or may be pre-defined (e.g., such as at thetime of manufacturing and/or prior to an examination of the object).

At 908, a first trajectory between a radiation source at a firstview-angle and a predefined location of a first detector cell isdetermined to identify a first intersection with the surface. That is,stated differently, a location on the surface where a first rayfollowing the first trajectory would intersect the surface isdetermined. In this way, data corresponding to the radiation source atthe first view-angle and yielded from the first detector cell can bemapped to the location on the surface where the first ray intersectedthe surface.

At 910, a second trajectory between the radiation source at the firstview-angle and a predefined location of a second detector cell isdetermined to identify a second intersection with the surface. That is,stated differently, a location on the surface where a second rayfollowing the second trajectory would intersect the surface isdetermined. In this way, data corresponding to the radiation source atthe first view-angle and yielded from the second detector cell can bemapped to the location on the surface where the second ray intersectedthe surface.

At 912, a third trajectory between the radiation source at a secondview-angle and the predefined location of the first detector cell isdetermined to identify a third intersection with the surface. That is,stated differently, a location on the surface where a third rayfollowing the third trajectory would intersect the surface isdetermined. In this way, data corresponding to the radiation source atthe second view-angle and yielded from the first detector cell can bemapped to the location on the surface where the third ray intersectedthe surface.

At 914, a fourth trajectory between the radiation source at a secondview-angle and the predefined location of the second detector cell isdetermined to identify a fourth intersection with the surface. That is,stated differently, a location on the surface where a fourth rayfollowing the fourth trajectory would intersect the surface isdetermined. In this way, data corresponding to the radiation source atthe second view-angle and yielded from the second detector cell can bemapped to the location on the surface where the fourth ray intersectedthe surface.

At 916 in the example method 900, a projection image is generated usingthe volumetric data. The projection image is generated based uponidentifying the first intersection, the second intersection, the thirdintersection, and the fourth intersection. By way of example, a firstportion of the volumetric data generated by the first detector cellduring a first view (e.g., while the radiation source is at the firstview-angle) may be used to determine a characteristic(s) of a firstpixel of the projection image representing a portion of the surfacecomprising the first intersection. As another example, a second portionof the volumetric data generated by the second detector cell during thefirst view may be used to determine a characteristic(s) of a secondpixel of the projection image representing a portion of the surfacecomprising the second intersection. As yet another example, a thirdportion of the volumetric data generated by the first detector cellduring the second view may be used to determine a characteristic(s) of athird pixel of the projection image representing a portion of thesurface comprising the third intersection.

The example method 900 ends at 918.

In some embodiments, a plurality of projection images may be generatedfor an object by defining multiple surfaces within the object (e.g.,where respective projection images are focused on a different surface)and/or by generating sliced projection images which respectively depicta projection of merely a slice of the object.

Referring to FIG. 10, an example method 1000 for generating a slicedprojection image is described. The example method 1000 begins at 1002,and volumetric data yielded from volumetrically examining an object viaradiation is acquired at 1004.

At 1006, the volumetric data is reconstructed (e.g., such as by anobject analysis component 122 in FIG. 1) to generate a volumetric image.Example reconstruction techniques include, among other things,back-projection, iterative reconstruction, tomosynthesis reconstruction,and/or other analytical or iterative approaches for convertingvolumetric data from projection space to image space.

At 1008 in the example method 1000, a slice of the volumetric image thatis of interested is removed from the volumetric image to generate azeroed volumetric image. By way of example, voxels representing a sliceof the object that is of interest may be zeroed or otherwise clearedsuch that the data relating to such voxels is separated from datarelating to voxels that do not represent the slice.

At 1010 in the example method 1000, the zeroed volumetric image isforward projected to generate a forward projection. That is, voxels ofthe volumetric image that were not zeroed are forward projected togenerate the forward projection using analytic and/or iterativetechniques that convert the zeroed volumetric image from image space toprojection space.

At 1012, the volumetric data is compared to the forward projection toidentify a portion of the volumetric data representative of the slice ofthe volumetric image that is of interest. By way of example, the forwardprojection is subtracted from the volumetric data to identify adifference. Such a difference may be extracted from the volumetric datato generate volumetric data indicative of a slice of the volumetricimage that is of interest. In this way, a portion of the volumetric datathat is representative of a slice of the object that is of interest maybe separated from the remaining volumetric data.

At 1014, the volumetric data indicative of the slice of the volumetricimage that is of intersect is mapped to a surface laying within theslice of the volumetric image that is of interest to generate a slicedprojection image, such as using one of the foregoing techniquesdescribed with respect to FIGS. 3-9.

The example method 100 ends at 1016.

Still another embodiment involves a computer-readable medium comprisingprocessor-executable instructions configured to implement one or more ofthe techniques presented herein. An example computer-readable mediumthat may be devised in these ways is illustrated in FIG. 11, wherein theimplementation 1100 comprises a computer-readable medium 1102 (e.g., aflash drive, CD-R, DVD-R, application-specific integrated circuit(ASIC), field-programmable gate array (FPGA), a platter of a hard diskdrive, etc.), on which is encoded computer-readable data 1104. Thiscomputer-readable data 1104 in turn comprises a set ofprocessor-executable instructions 1106 configured to operate accordingto one or more of the principles set forth herein. In one suchembodiment 1100, the processor-executable instructions 1106 may beconfigured to perform a method 1108 when executed via a processing unit,such as at least some of the example method 800 of FIG. 8, at least someof the example method 900 of FIG. 9, and/or at least some of the examplemethod 1000 of FIG. 10, for example. In another such embodiment, theprocessor-executable instructions 1106 may be configured to implement asystem, such as at least some of the exemplary environment 100 of FIG.1, for example. Many such computer-readable media may be devised bythose of ordinary skill in the art that are configured to operate inaccordance with one or more of the techniques presented herein.

Moreover, “exemplary” is used herein to mean serving as an example,instance, illustration, etc., and not necessarily as advantageous. Asused in this application, “or” is intended to mean an inclusive “or”rather than an exclusive “or”. In addition, “a” and “an” as used in thisapplication are generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform. Also, at least one of A and B and/or the like generally means A orB or both A and B. Furthermore, to the extent that “includes”, “having”,“has”, “with”, or variants thereof are used in either the detaileddescription or the claims, such terms are intended to be inclusive in amanner similar to the term “comprising”.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims.

As used in this application, the terms “component,” “module,” “system”,“interface”, and the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a controller and the controller can be a component. One or morecomponents may reside within a process and/or thread of execution and acomponent may be localized on one computer and/or distributed betweentwo or more computers.

Furthermore, the claimed subject matter may be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. Of course, those skilled inthe art will recognize many modifications may be made to thisconfiguration without departing from the scope or spirit of the claimedsubject matter.

Further, unless specified otherwise, “first,” “second,” and/or the likeare not intended to imply a temporal aspect, a spatial aspect, anordering, etc. Rather, such terms are merely used as identifiers, names,etc. for features, elements, items, etc. (e.g., “a first channel and asecond channel” generally corresponds to “channel A and channel B” ortwo different (or identical) channels or the same channel).

Although the disclosure has been shown and described with respect to oneor more implementations, equivalent alterations and modifications willoccur to others skilled in the art based upon a reading andunderstanding of this specification and the annexed drawings. Thedisclosure includes all such modifications and alterations and islimited only by the scope of the following claims. In particular regardto the various functions performed by the above described components(e.g., elements, resources, etc.), the terms used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (e.g., that is functionally equivalent), even though notstructurally equivalent to the disclosed structure which performs thefunction in the herein illustrated example implementations of thedisclosure. Similarly, illustrated ordering(s) of acts is not meant tobe limiting, such that different orderings comprising the same ofdifferent (e.g., numbers) of acts are intended to fall within the scopeof the instant disclosure. In addition, while a particular feature ofthe disclosure may have been disclosed with respect to only one ofseveral implementations, such feature may be combined with one or moreother features of the other implementations as may be desired andadvantageous for any given or particular application.

What is claimed is:
 1. A method for generating a projection image fromvolumetric data, comprising: acquiring volumetric data yielded from anexamination of an object via radiation; defining a surface about which aprojection image of the object is focused; mapping a first portion ofthe volumetric data, corresponding to a first view, to the surface;mapping a second portion of the volumetric data, corresponding to asecond view, to the surface; and generating a projection image basedupon the mapping a first portion and the mapping a second portion. 2.The method of claim 1, the mapping a first portion comprising:determining a first trajectory between a radiation source emitting theradiation during the first view and a predefined location on a firstdetector cell; identifying a first intersection between the firsttrajectory and the surface; and mapping first data yielded from thefirst detector cell and corresponding the first view to the firstintersection.
 3. The method of claim 2, the mapping a first portioncomprising: determining a second trajectory between the radiation sourceduring the first view and a predefined location on a second detectorcell; identifying a second intersection between the second trajectoryand the surface; and mapping second data yielded from the seconddetector cell and corresponding to the second view to the secondintersection.
 4. The method of claim 3, comprising: determining a firstcharacteristic of a first pixel of the projection image based upon thefirst data; and determining a second characteristic of a second pixel ofthe projection image based upon the second data.
 5. The method of claim2, the mapping a second portion comprising: determining a secondtrajectory between the radiation source during the second view and thepredefined location on the first detector cell; identifying a secondintersection between the second trajectory and the surface; and mappingsecond data yielded from the first detector cell and corresponding tothe second view to the second intersection.
 6. The method of claim 5,the first trajectory different than the second trajectory.
 7. The methodof claim 5, comprising: determining a first characteristic of a firstpixel of the projection image based upon the first data; and determininga second characteristic of a second pixel of the projection image basedupon the second data.
 8. The method of claim 7, wherein at least one ofthe first characteristic or the second characteristic is an intensitycharacteristic.
 9. The method of claim 1, wherein the volumetric datarepresents merely a slice of the object.
 10. The method of claim 1,wherein the surface is planar.
 11. The method of claim 1, wherein thesurface is non-planar.
 12. The method of claim 1, the defining a surfacecomprising: identifying, based upon the volumetric data, a region of theobject that is of interest; and defining the surface based upon theregion of the object that is of interest.
 13. The method of claim 1,wherein: the mapping a first portion comprises: determining a firsttrajectory between a radiation source emitting the radiation during thefirst view and a predefined location on a first detector cell;identifying a first intersection between the first trajectory and thesurface; mapping first data yielded from the first detector cell andcorresponding the first view to the first intersection; determining asecond trajectory between the radiation source during the first view anda predefined location on a second detector cell; identifying a secondintersection between the second trajectory and the surface; and mappingsecond data yielded from the second detector cell and corresponding tothe second view to the second intersection; and the mapping a secondportion comprises: determining a third trajectory between the radiationsource during the second view and the predefined location on the firstdetector cell; identifying a third intersection between the thirdtrajectory and the surface; and mapping third data yielded from thefirst detector cell and corresponding to the second view to the thirdintersection.
 14. A method for generating a projection image fromvolumetric data, comprising: acquiring volumetric data yielded from anexamination of an object via radiation; defining a surface about which aprojection image of the object is focused; for a first view: determininga first trajectory between a radiation source emitting the radiationduring the first view and a predefined location on a first detectorcell; identifying a first intersection between the first trajectory andthe surface; and mapping a first portion of the volumetric data, yieldedfrom the first detector cell and corresponding to the first view, to thefirst intersection; for a second view: determining a second trajectorybetween the radiation source during the second view and the predefinedlocation on the first detector cell; identifying a second intersectionbetween the second trajectory and the surface; and mapping a secondportion of the volumetric data, yielded from the first detector cell andcorresponding to the second view, to the second intersection; andgenerating a projection image based upon the mapping a first portion andthe mapping a second portion.
 15. The method of claim 14, comprising:determining a third trajectory between the radiation source during thefirst view and a predefined location on a second detector cell;identifying a third intersection between the third trajectory and thesurface; and mapping a third portion of the volumetric data, yieldedfrom the second detector cell and corresponding to the first view, tothe third intersection.
 16. The method of claim 15, the generatingcomprising generating the projection image based upon the mapping athird portion.
 17. The method of claim 14, the generating comprising:determining a first characteristic of a first pixel of the projectionimage based upon the first portion; and determining a secondcharacteristic of a second pixel of the projection image based upon thesecond portion.
 18. A method, comprising: extracting, from volumetricdata yielded from an examination of an object via radiation, a portionof the volumetric data indicative of a slice of the object that is ofinterest; defining a surface about which a sliced projection image ofthe slice is focused; mapping a first portion of the portion of thevolumetric data, corresponding to a first view, to the surface; mappinga second portion of the portion of the volumetric data, corresponding toa second view, to the surface; and generating the sliced projectionimage based upon the mapping a first portion and the mapping a secondportion.
 19. The method of claim 18, the extracting comprising:reconstructing the volumetric data to yield a volumetric imagerepresenting the object; remove a portion of the volumetric imagerepresentative of the slice to generate a zeroed volumetric image;forward projecting the zeroed volumetric image to generate a forwardprojection; and comparing the forward projection to the volumetric data.20. The method of claim 19, the comparing comprising: subtracting theforward projection from the volumetric data to identify the portion ofthe volumetric data indicative of the slice of the object that is ofinterest.